The present invention relates generally to the field of automated entity, data processing, system control, and data communications, and uses any number of distinct techniques to provide a an integrated system for analyzing data, discovering likely data relationships, and constructing models based on that data. Specifically, the KEE is a system for automatically learning models from data. The learned models can be used in a variety of ways: They may be used to provide automatic classification of data, based on a given set of classifications from training examples; they may be used to predict numeric values, based on the values from some training set; and they may be used to describe commonalities or functional relationships among the data. In many cases, data mining is used both for prediction and for description. For instance, a regression line is a model of the behavior of a single output to one or more inputs, and can be used both to predict an output, given an input tuple, and to describe the function relating a dependent variable to an abstraction representing all possible tuples of input variables. Thus, the regression technique is appropriate for many model generation goals, including estimation, prediction, characterization, and summarization. Many other techniques share this broad applicability, though some are particularly well suited to one or more prediction tasks, and some are particularly well suited to descriptive tasks.